Abstract
Increasing the performance of cloud downloading service in a peer-peer network by efficient mode selection method. Using P2P to download video content often faces challenges like high bandwidth requirement, dealing with a huge number of peer requests, resulting in inefficient system performance. The latest premium service to have been developed is the cloud downloading. In this service, cloud storage is used to store the video content. The server is used to cache the user interested video content and also update the cache based on the peer request. Efficient Video content downloading using the P2P approach is accessible, but does not always give good concert. The cloud storage and server caches user-attracted content and updates the cache based on user downloading requirements. If a requested video is not in the cache, the request is detained in a waiting state until the cache is efficient. In this study, an alternative mode is proposed. The model contains the two modes named as server mode and helper mode. These two modes are integrated in cloud downloading service. Server mode is used for enhancing video content distribution in cloud storage. Helper mode is used to provide the user with the requested video content as soon as the peer request arrives. The two modes automatically switch between each other, based on the peer request. If the requested content is a popular video, helper mode provides the content. Whereas, the content is provided by the server mode if the requested content is unpopular. These two modes achieve good performance.
Highlights
The principle of cloud download has helped in achieving high quality video content distribution by using cloud utilities
This study aims at minimizing the average Shortest Path Betweeness Centrality (SPBC) and assigns each user a cloud, satisfying Quality of Service (QoS) requirements by assigning each end user at least one cloud site (Papagianni et al, 2013)
A way to respond to a large number of user requests using virtual machines is a challenge. We address this challenge with VMThunder, a new VM tool and speed up VM image streaming by integrating Peer-to-Peer (P2P) streaming techniques (Zhang et al, 2014)
Summary
The principle of cloud download has helped in achieving high quality video content distribution by using cloud utilities. When the user sends video request to the cloud, the cloud downloads the video from the internet and stores it in cloud cache. The user retrieves the requested video with high data rate in any place at any time via the intra cloud data transfer system (named video cloud) (Huang et al, 2011). Varying storage at the data sources compares the performance of the policies and has an impact in storage availability. We propose Liquid, a distributed file system that has a client side breaking the VM images into small data blocks, referencing them by their fingerprints and using deduplication techniques and saving them into meta server. In this study we design VMThunder, a fast VM image provisioning tool for deploying a VM at a large scale that downloads only the on demand
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